China’s rapid advancement in Artificial Intelligence (AI), particularly fueled by tech giants like Alibaba, Baidu, Tencent, and iFlytek, is increasingly influenced by open-source collaboration. Models such as Alibaba’s Qwen 3 series and Qwen 2.5, which rival GPT-4 Turbo in performance, are built on open frameworks, encouraging developer contributions and cross-platform integration. Qwen is hailed as the "king of open source" and is also among the top three contributors to the global open-source AI ecosystem.
The Rise of China’s Open-Source Model
Baidu’s ERNIE series, including the popular ERNIE Bot, and Tencent’s Hunyuan model benefit from China’s broader AI ecosystem, where research institutions, startups, and industry players openly share tools, datasets, and model architectures. Similarly, iFlytek’s Spark 4.0 Turbo demonstrates exceptional benchmark performance, reflecting the success of this multi-participant, open-innovation strategy.
In contrast to the more closed and proprietary models prevalent in the United States, China’s strategy leverages state support and open-source infrastructure to accelerate collective progress. This allows Chinese companies to massively build, iterate, and deploy foundation models while fostering a unique domestic AI ecosystem. This progress not only indicates China’s efforts to enhance its AI capabilities by circumventing reliance on Western supply chains but also highlights Beijing’s ambitious role in shaping the future of global AI governance.
Strategic Shift: Open Source as an Economic Tactic
Instead of retaliatory export controls in response to U.S. efforts to block its access to critical technologies, China aims to adopt a decentralized approach to ensure the long-term security of its industrial base. China’s strategic shift toward open-source AI development, in this context, resonates with a guerrilla economics strategy. This strategy is characterized by China’s efforts to identify vulnerabilities in global supply chains, deepen connections with countries in the Global South, and showcase its domestic innovations as a better alternative to Western technologies – one that is more collaborative, decentralized, democratic, and accessible.
China prioritizes AI as a key national objective not only to enhance national competitiveness but also to demonstrate its private sector’s ability to thrive under state control. The evolving U.S.-China AI competition now centers on how the private sector will lead this innovation game, which methods will be leveraged to spearhead the next wave of AI innovation, and how global powers – including medium-sized and emerging AI powers – will respond.
Advantages and Challenges of China’s Open-Source AI
Underpinning this evolving policy stance is China’s vigorous advocacy of its open-source model as an ideological tool to eclipse the importance of Western technology. China is rapidly positioning itself as a leader in shaping international AI governance norms and frameworks that align with the needs of small and emerging AI powers. Chinese President Xi Jinping stated at last year’s G20 summit that AI development "should not be a game for the rich countries." China has repeatedly raised the issue of inclusive AI governance through its AI capacity-building action plan and global platforms such as the United Nations AI resolution. This approach helps strengthen China’s influence in the intensifying race to shape AI standards and frameworks.
China’s increasing emphasis on open-source AI enables it to expand alternatives that rely less on Western supply chains and licensing regimes. This strategy not only enhances China’s technological resilience in the face of export controls but also positions it as a credible player in promoting alternative norms and frameworks for global AI governance.
China’s AI diplomacy, aligned with its indigenous technology development model, may undermine the existing influence of Western norms. Despite the United States championing liberal democratic ideals, its reliance on closed-source AI models may limit its ability to lead global conversations on inclusive and collaborative AI development.
Structural Differences and Future Outlook
These differences in models, however, reflect deeper structural divergences. As AI governance debates intensify, China’s open-source exports may broaden its normative influence, but questions remain about the transparency, data integrity, and trustworthiness of these models. Furthermore, while China’s broader claims about AI advancements appear promising, the story of DeepSeek alone is not genuine proof of China’s success. While crucial details and data for model training remain hidden, the company’s compliance with state laws requires global scrutiny. Some European countries have already banned the platform for their users, citing privacy and data transfer risks.
Meanwhile, the U.S. faces the challenge of balancing commercial interests with the need to cooperate on open and responsible AI standards globally. While Western technologies often claim to be harbingers of liberal democratic principles, their export models are primarily driven by acts of corporate imperialism that tend to extract resources and human labor from countries in the Global South.
This evolving competition suggests that neither the Chinese nor the U.S. model is absolute, and leadership in future AI governance may depend on each country’s ability to adapt and bridge these competing approaches. As both countries appear to be reinforcing their existing power structures and seeking to uphold their ideological principles, a truly global AI development framework needs to be built on shared governance, responsible and equitable access, multilateral cooperation, and a balance between security and progress.
Practical Examples of China’s Open-Source AI
Alibaba’s Qwen series is an excellent example showcasing China’s rapid development in open-source AI. These models not only compete in performance with some of the most advanced proprietary AI models, but also encourage the participation and improvement of global developers by opening their source code and architecture. This model promotes rapid iteration and innovation of technology, enabling Qwen to quickly adapt to different application scenarios and attract a large developer community.
Another notable case is ERNIE Bot under Baidu. As China’s leading search engine and AI technology provider, Baidu has leveraged its strong technological capabilities and massive datasets to develop ERNIE Bot, an AI model with broad application prospects. Similar to Qwen, ERNIE Bot also adopts an open-source strategy, allowing developers to conduct secondary development and customization based on it, thereby promoting the application of AI technology in various industries.
Challenges and Opportunities Facing China’s Open-Source AI
While China’s open-source AI model has many advantages, it also faces some challenges. One of the main challenges is data security and privacy protection. Since AI model training requires large amounts of data, ensuring data security and user privacy has become an important issue. In addition, the openness of open-source AI may also lead to malicious use and abuse, such as for developing false information and cyberattacks.
However, these challenges also bring opportunities. By establishing sound data security and privacy protection mechanisms, as well as strengthening the supervision and management of open-source AI projects, risks can be effectively reduced, and the healthy development of open-source AI can be promoted. At the same time, the openness and collaboration of open-source AI also provide greater space for innovation, which can attract global developers and researchers to participate together and promote the rapid advancement of AI technology.
Far-Reaching Impact of China’s Open-Source AI
China’s open-source AI model is not only of great significance to China’s own development, but also has a far-reaching impact on the global AI industry and governance. First, it breaks the monopoly of Western countries in the field of AI technology and provides more choices and opportunities for developing countries. Second, it promotes the exchange and cooperation of global AI technology and promotes the popularization and application of AI technology. Finally, it also poses new challenges and opportunities for global AI governance, requiring countries to work together to establish a more open, inclusive, cooperative, and responsible AI governance system.
Overall, China’s open-source AI strategy is an innovative and strategic approach that not only helps China enhance its AI capabilities, but also has a far-reaching impact on the global AI industry and governance. Although facing some challenges, as long as it can be effectively addressed, China’s open-source AI model is expected to lead the future direction of AI development and bring more opportunities and well-being to the world.
Open-Source AI: Building a More Inclusive Future?
China’s increasing emphasis on open-source AI is not just a technological strategy; it reflects a broader approach to shaping a more inclusive and collaborative future for global AI governance. By promoting open-source models, China aims to break down the barriers of proprietary technology controlled by a few Western nations. This approach is particularly appealing to emerging and developing countries that may lack the resources or infrastructure to build their own AI models from scratch.
Open-source AI, by providing access to source code, datasets, and algorithms, empowers these countries to participate in the development and deployment of AI and to tailor solutions to their specific needs and contexts. This decentralized approach can foster innovation, nurture local capabilities, and address the growing digital divide in the AI landscape.
Concerns About Data Integrity and Trust
Despite the potential benefits of open-source AI, it is important to address concerns associated with it, particularly regarding data integrity and trust. Because open-source models rely on community contributions, there is a risk that malicious actors could introduce flawed or biased data or algorithms. This could lead to unreliable or inaccurate results, undermining trust in the models.
To mitigate these risks, it is essential to implement robust quality control mechanisms and verification procedures. This could include establishing review processes, ensuring data transparency, and promoting responsible coding practices. Furthermore, collaboration and knowledge sharing are crucial for identifying and correcting potential vulnerabilities in open-source models.
Evolving Norms of AI Governance
As open-source AI gains traction, it will play an increasingly important role in shaping global AI governance norms. China has been actively advocating for a more inclusive and collaborative approach to AI governance in international forums, emphasizing the need to consider the needs and perspectives of emerging and developing countries.
By promoting open-source AI, China aims to challenge the existing influence of Western norms on AI governance and to foster a framework that is more reflective of the shared interests of all nations and stakeholders. This approach has the potential to promote a more equitable and just AI development, ensuring that the benefits of AI are shared by all.
Balancing Commercial Interests With Global Cooperation
The challenge for the United States and its allies lies in balancing commercial interests with the need to cooperate globally on open and responsible AI standards. While proprietary AI models may offer competitive advantages and financial gains, they also risk perpetuating the digital divide by limiting access to AI technologies and expertise for emerging and developing nations.
Adopting a more open and collaborative approach, including supporting open-source AI, can help bridge this gap and foster a more inclusive and equitable global AI ecosystem. This requires a rethinking of intellectual property and technology transfer, as well as a commitment to shared governance and multilateral cooperation.
Shared Responsibility
China’s open-source strategy is not without risk, but it offers a unique window of opportunity. Like any technology, it has the potential to be deployed for good and equally be deployed for “bad.” However, with robust global governance frameworks, ethical guardrails, and a culture of open source, the world has not only a stronger opportunity to shape the trajectory of the technology, but to reshape its collective future.
Ensuring that AI benefits everyone, everywhere will require closer collaboration than ever before.